Process flowcharting meets simulation modeling
Article Abstract:
A new generation of user-friendly process-simulation programs aims to assist users in modeling and simulating nonmanufacturing functions including order fulfillment, sales and marketing, product development, workflow and accounting. These manufacturing simulation software enable users to test assumptions before introducing changes to a process. Simple to use and relatively low-cost at prices ranging from $500 to $1,000, they are a drastic departure from previous simulation programs which are expensive and difficult to use. They are Process Charter, ProcessModel, Optima! and ClearProcess 1.0.
Publication Name: Quality
Subject: Engineering and manufacturing industries
ISSN: 0360-9936
Year: 1996
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Automation can make your SPC charts send wrong messages
Article Abstract:
Processes improved via automation can generate autocorrelated data which can cause Shewhart charts to reflect errors despite no changes in the process. A model of autocorrelated process performance and monitor deviations from this model can be built to solve problems emanating from automatically controlled processes. The model is x(t) = 1.3950 + 0.5303(x(t-1)), which makes use of regression analysis. A modified X-bar chart for transmission cover diameters has no out-of-control points, appropriate to unchanging processes.
Publication Name: Quality
Subject: Engineering and manufacturing industries
ISSN: 0360-9936
Year: 1992
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Quality improvement begins with product data
Article Abstract:
The interpretation of statistical process control data (SPC) utilizing a statistical versus a scientific approach is examined. Statistical analysis of data implies literal translation and instantaneous action, while scientific interpretation implies learning what action is required before implementation. In the literal approach, process variables are monitored and output is controlled, but in the scientific approach, output of a process is analyzed to detect process disturbances.
Publication Name: Quality
Subject: Engineering and manufacturing industries
ISSN: 0360-9936
Year: 1993
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